Systems and methods for aggregating content

ABSTRACT

A method for producing an audio representation of aggregated content includes selecting preferred content from a number of sources, wherein the sources are emotion-tagged, aggregating the emotion-tagged preferred content sources, and creating an audio representation of the emotion-tagged aggregated content.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of the parent application U.S. patentapplication Ser. No. 15/445,202, filed on Feb. 28, 2017 entitled“SYSTEMS AND METHODS FOR AGGREGATING CONTENT”, and claims priority toU.S. Provisional Patent Application No. 62/440,591, filed Dec. 30, 2016,the contents of both are hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure generally relates to data communication over anetwork. More particularly, the following discussion relates to systems,methods, and devices for producing audio representations of aggregatedcontent.

BACKGROUND

It is often desirable for users to consume aggregated content availablefrom a number of websites and other sources over a network, such as theInternet. For example, rather than relying on a single website newssource, many users prefer to read content compiled from multiple, lessmainstream news sites.

Furthermore, many users consume news and other information while drivingor engaging in other activities that do not permit such news to be readdirectly. While audiobooks and other means of performing text-to-speechconversion exist, such systems tend to produce overly mechanical,unemotional readings of such text, resulting in an unsatisfactorylistening experience.

Accordingly, there is a need for improved methods of producing andconsuming audio representations of content gathered from networksources. These and other desirable features and characteristics willbecome apparent from the subsequent detailed description and the claims,taken in conjunction with the accompanying drawings and this backgroundsection.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

Exemplary embodiments will hereinafter be described in conjunction withthe following drawing figures, wherein like numerals denote likeelements, and:

FIG. 1 is a conceptual block diagram illustrating a network inaccordance with one embodiment.

FIG. 2 is a conceptual block diagram depicting the producing ofaggregated audio content in accordance with one embodiment.

FIG. 3 is a conceptual block diagram depicting the producing ofaggregated audio content in accordance with another embodiment.

FIG. 4 is a conceptual block diagram depicting the producing ofaggregated audio content in accordance with one embodiment.

FIGS. 5-6 are flowcharts illustrating methods in accordance with variousembodiments.

FIGS. 7 and 8 depict various ways of characterizing speech-to-textemotional states in accordance with one or more embodiments.

DETAILED DESCRIPTION

Systems and methods are provided for producing audio representations ofaggregated content. In accordance with various embodiments, the textcontent used for aggregation (e.g., the aggregated content itself, orthe individual text source) include “emotion tags” or othermeta-information indicating how the text content should be read. Theseemotion tags are then used in the text-to-speech process to produce anaudio representation of the aggregated content that includes emotion,thereby improving the listening experience for the user.

Referring to FIG. 1, one or more audio playback devices (or simply“devices”) 106 is configured to receive and process media content fromone or more content sources (or simply “sources”) 108 (e.g., 108 a-d).Device 106 may correspond to any combination of hardware and softwareconfigured to receive and process media content from a content source(e.g., one or more of content servers 108), including, for example, amotor vehicle media system, a mobile smart-phone, a computer system(such as desktop computer, laptop computer, tablet computer, or thelike), a set top box, a television monitor, a place-shifting device, atelevision receiver, a dedicated media player, or the like. Similarly,sources 108 (e.g., 108 a-d) include any combination of hardware andsoftware configured to provide content (e.g., audio and/or visualcontent) to device 106 over network 102. In some embodiments, sources108 are servers providing web content (e.g., via HTML, CSS, Javascript,etc.), including text-based news content. Also shown in FIG. 1 is acomputing device 104 (including a processor, storage, memory, etc.)configured to request and receive content from sources 108, process thatcontent, and provide aggregated content (in audio form) to device 106,as discussed in further detail below.

While the environment illustrated in FIG. 1 is shown as a single network150, in practice the environment may include any number of wired and/orwireless network operating within the geographic proximity of a home,office or other structure and that are generally under the control of asingle user, family or operator (e.g., a WLAN, the Internet, and thelike).

Device 106 may be any device, component, module, hardware and/or thelike that is capable of communicating with the server 104 over network102. As mentioned above, depending on the embodiment, client device 304may be realized as a motor vehicle media system, a conventional personalcomputer, portable computer, a tablet computer, workstation and/or othercomputing system, a mobile (or cellular) telephone, a smartphone, apersonal digital assistant, a video game player, and/or any other devicecapable of receiving content from sources 108 and presenting audioand/or visual content. In this regard, the device 106 includes a displaydevice, such as a monitor, screen, or another conventional electronicdisplay, capable of graphically presenting visual and audio content,data and/or information that is generated or otherwise provided 104. Thedevice 106 may further include a user input device, such as a keyboard,a mouse, a touchscreen, or the like, capable of receiving input dataand/or other information from the user of the device 106. The device 106also includes a processing system and a data storage element (or memory)that is coupled to or otherwise accessed by the processing system andstores programming instructions (e.g., an application downloadable overan “app store”). The processing system may be realized as any sort ofprocessor, microprocessor, microcontroller, digital signal processor, orany other suitable processing device, or any suitable combinationthereof. The device 106 may reside at a geographic location that isremote or otherwise physically distinct from the geographic location ofthe servers 104 and content sources 108.

Device 106 and or server 104 may execute a conventional browser or otherclient application that is compatible with standard Internet, world wideweb (WWW), transmission control protocol, and/or Internet Protocol(TCP/IP), and/or other formats. Such browsers are typically capable ofdisplaying active or other documents formatted in accordance withpublished protocols and/or computer languages (e.g., hypertext markuplanguage (HTML), extensible markup language (XML), cascading stylesheets (CSS), Javascript, and/or the like). Many browsers are alsocapable of executing “plugin” applications, applets or the like. Suchplugins may be formatted in accordance with ActiveX, JAVA, Javascriptand/or any number of other formats. A number of commonly used webbrowsers are available for a number of different computing platforms,and the subject matter described herein is not limited to any particularbrowser application. In the illustrated embodiment, device 106 furtherincludes a media player application. The media player may be astandalone media player, or the media player may be implemented as aplugin or other applet that runs within the device 106 as desired. Insome embodiments, the media player is initially obtained from anetworked host, such as server 104. The media player may be retrieved onan as-needed basis in some embodiments, or may be stored at device 106for subsequent execution.

In the illustrated embodiment, server 104 may be realized as one or moreserver computers or other device(s) coupled to the network 102 andcapable of interacting with the device 106 and content sources 108. Theserver 104 may be implemented with a server computer system or dataprocessing system that is based upon any processor, architecture and/oroperating system, and will typically be implemented using a processingsystem, memory, and input/output features. Various embodiments may beimplemented using dedicated or shared hardware servers; otherimplementations may make use of virtual server features as part of a“cloud computing” service, such as any of the cloud computing servicesprovided by any number of providers.

While FIG. 1 illustrates a single server 104, many practical embodimentsof the system 300 may provide a cluster or other collection of multiplehost servers to support any desired number of simultaneouscommunications with multiple clients and/or multiple media devices. Thiscluster may also incorporate appropriate routing, load balancing, accessand security mechanisms and or any number of other features. In variousembodiments, each server 104 is an actual or virtual computer systemexecuting an operating system in conjunction with a processing system,memory and/or I/O features to provide a computing core that is capableof executing a portal application, as well as any number of daemons,processes, applications or other modules as desired.

The user of the device 106 is able to direct server 104 (e.g., via aconfiguration step intended to select desired content sources 108) toconnect to the portal application supported by content sources 108 viathe network 102, for example, by directing a client application to a URLor other network address associated with sources 108.

Referring now to FIG. 2, in one embodiment, one or more text (or HTML)content from content sources 208A, 208B, and 208C, each including“emotion tagging” as discussed in further detail below) is aggregatedinto emotion-tagged aggregated content 210. Emotion-tagged aggregatedcontent 210 is then converted (via a suitable text-to-speech conversion215) to an audio file (or audio representation) of emotion-taggedaggregated content 210.

FIG. 3 depicts another embodiment in which the content sources 208A-Bare not themselves emotion-tagged, but rather such tagging is performedafter aggregation. That is, aggregated content 310 undergoes a taggingprocess 315 (e.g., a manual process, an automatic machine-learning modelprocess, etc.) to produce emotion-tagged aggregated content 320. Thisaggregated content 320 is then subjected to text-to-speech conversion toproduce an audio file of aggregated content 330 that can then be playedby a user via device 106.

FIG. 4 depicts yet another embodiment in which each content source 208has been emotion-tagged, but is individually converted to audio viaindividual text-to-speech conversions 401, resulting in correspondingaudio files (of non-aggregated content) 408A, 408B, and 408C. Theseindividual audio files are then themselves aggregated to form aggregatedaudio content 410.

FIG. 5 is a flowchart illustrating a method 500 corresponding to theembodiment depicted in FIG. 2. As illustrated, this method includesfirst (501) selecting preferred content from a plurality of sources,wherein the sources are emotion-tagged, aggregating the emotion-taggedpreferred content sources (502), and then creating (assembling, editing,mixing, etc.) an audio representation of the emotion-tagged aggregatedcontent (503).

FIG. 6 is a flowchart illustrating a method 600 corresponding to theembodiment depicted in FIG. 3. As illustrated, this method includesfirst (601) selecting preferred content from a plurality of sources,wherein the sources are not emotion-tagged, aggregating the preferredcontent sources (602), creating emotion-tagged aggregated content (603),then creating (assembling, editing, mixing, etc.) an audiorepresentation of the emotion-tagged aggregated content (604).

FIG. 7 is a flowchart illustrating a method 700 corresponding to theembodiment depicted in FIG. 4. As illustrated, this method includesfirst (701) selecting preferred content from a plurality of sources,wherein the sources are emotion-tagged, creating audio of each of theemotion-tagged content sources (702), and then aggregating the audio ofthe emotion-tagged preferred content sources (703).

As used herein, the phrase “emotion-tagged” or “emotitag” or the likerefers to any embedded or meta-information specifying how text-to-speechconversion should take place (e.g., step 503 in FIG. 5). That is, thepurpose of the emotion tags is to produce audio that includes emotionsthat replicate the way that a news announcer, pundit, or other humanbeing might read the text.

In some embodiments, the content (e.g., the individual sources 108and/or the aggregated content 210) includes custom HTML tags, CSSstyles, XML tags, or the like that specify particular emotions. Withoutloss of generality, the following example is framed as custom HTML tags:<anger>I can't believe what congress just did</anger>. <sarcasm>The guywe all know and love started it all </sarcasm>. <vigilance>We must keepan eye on that guy</vigilance>. <awe>But thankfully our favorite newaddition is leading the charge </awe>. <acceptance>So perhaps everythingwill work out OK.</acceptance>.

The number and type of emotional tags may vary, depending upon designconsiderations. FIG. 8, for example, depicts what is known as thePlutchick wheel of emotions, which may be used in determiningappropriate emotion tags. FIG. 9 depicts a simpler, Lovheim-cube-basedrepresentation of emotions that also may be used in determiningappropriate emotion tags. It will be appreciated that the emotiontaxonomies depicted in these figures are merely provided as an example,and that the range of possible embodiments is not so limited.

Regardless of the particular tags used, it will be appreciated that thevarious steps illustrated above may be performed by any combination ofserver 104 and 106. For example, device 106 may be provided withemotion-tagged text, whereupon it uses that text to convert it tosuitable speech. In other embodiments, server 104 performs these steps.In some embodiments, device 106 pulls content from content sources 108.In other embodiments, server 104 pulls and compiles the aggregatedcontent.

The audio file produced in connection with the illustrated steps may beany suitable format, including various uncompressed, lossles, lossy, orother formats. Suitable formats include, for example, WAV, MP3, AIFF,OGG, M4A, WMA, or any other suitable format. The audio may be streamedand/or downloaded onto device 106.

In addition to producing an audio version of the aggregated content, avisual representation of an avatar, human being, or other entity may becreated (and displayed to the user). That is, an animated avatar (e.g.,with moving lips and appropriate expression based on the emotion tags)may be used to “read” the news to the user using a display presentwithin device 106.

Selection of preferred sources may be performed by the user via asuitable user interface that allows the user to select the sources andoptionally specify a “weighting factor” or the like that controls howoften that source is used for the aggregated content. That is, the usermay specify that content from cnn.com should be given a relatively lowweight of “1”, while fox.com should be given a relatively high weight of“8”.

Many other modifications and enhancements could be provided in a widearray of alternate but equivalent embodiments. The term “exemplary” isused herein to represent one example, instance or illustration that mayhave any number of alternates. Any implementation described herein asexemplary is not necessarily to be construed as preferred oradvantageous over other implementations. While several exemplaryembodiments have been presented in the foregoing detailed description,it should be appreciated that a vast number of alternate but equivalentvariations exist, and the examples presented herein are not intended tolimit the scope, applicability, or configuration of the invention in anyway. To the contrary, various changes may be made in the function andarrangement of elements described without departing from the scope ofthe claims and their legal equivalents.

1. A method for producing an audio representation of aggregated audiocontent, the method including: selecting a set of preferred content froma plurality of sources, wherein the preferred content is emotion-tagged;converting each preferred content that is emotion-tagged to an audiofile; generating a set of audio files corresponding to each convertedpreferred content wherein each preferred content is individuallyconverted into the audio file; and creating an audio representation thatcomprises aggregated audio content based on a set of individuallyconverted audio files.
 2. The method of claim 1, wherein the aggregatingstep is performed by a mobile device wherein the corresponding audiofiles comprise non-aggregated content.
 3. The method of claim 1, whereinthe creating step is performed by a mobile device.
 4. The method ofclaim 1, wherein the emotion-tagged content includes text with HTML tagsthat specify how text-to-speech conversion should be performed inconnection with the creation step.
 5. The method of claim 1, furtherincluding providing a user interface that allows a user to specifyweights to be applied to plurality of sources to select the preferredcontent.
 6. The method of claim 1, wherein creating the audiorepresentation includes combining corresponding converted audio fileswherein each converted audio file corresponds to a separate one of theplurality of sources.
 7. The method of claim 1, wherein theemotion-tagged content is tagged in accordance with at least one of aPlutchik or a Lovheim-cube-based emotion representation.
 8. A mediadevice including a processor configured to execute machine-readablesoftware instructions that cause the processor to produce an audiorepresentation of aggregated content by performing the steps of:selecting a set of preferred content from a plurality of sources,wherein the preferred content is emotion-tagged; converting eachpreferred content that is emotion-tagged to an audio file; andgenerating a set of audio files corresponding to each convertedpreferred content wherein each preferred content is individuallyconverted into the audio file wherein the generated set comprisesnon-aggregated content.
 9. The media device of claim 8, wherein theemotion-tagged content includes text with HTML tags that specify howtext-to-speech conversion should be performed in connection with thecreation step.
 10. The media device of claim 8, further wherein theprocessor provides a user interface that allows a user to specifyweights to be applied to plurality of sources to select the preferredcontent.
 11. The media device of claim 8, wherein the audiorepresentation includes a combination of non-aggregated audio files,each corresponding to a separate one of the plurality of sources. 12.The media device of claim 8, wherein the emotion-tagged content istagged in accordance with at least one of a Plutchik or aLovheim-cube-based emotion representation.
 13. A computer-implementedmethod for producing an audio representation of aggregated content, themethod including the steps of: selecting a set of preferred content froma plurality of sources, wherein the preferred content is emotion-tagged;converting each preferred content that is emotion-tagged to an audiofile; and generating a set of audio files corresponding to eachconverted preferred content wherein each preferred content isindividually converted into the audio file selecting preferred contentfrom a plurality of sources.
 14. The computer-implemented method ofclaim 13, wherein the aggregating step is performed by a mobile device.15. The computer-implemented method of claim 13, wherein the creatingstep is performed by a mobile device.
 16. The computer-implementedmethod of claim 13, wherein the emotion-tagged content includes textwith HTML tags that specify how text-to-speech conversion should beperformed in connection with the creation step.
 17. Thecomputer-implemented method of claim 13, further wherein the processorprovides a user interface that allows a user to specify weights to beapplied to plurality of sources to select the preferred content.
 18. Thecomputer-implemented method of claim 13, wherein the audiorepresentation includes a combination of non-aggregated audio files,each corresponding to a separate one of the plurality of sources. 19.The computer-implemented method of claim 13, wherein the emotion-taggedcontent is tagged in accordance with at least one of a Plutchik or aLovheim-cube-based emotion representation.
 20. The computer-implementedmethod of claim 13, wherein the processor is further configured toproduce a visual representation of an avatar reading aloud the audiorepresentation of the emotion-tagged individually aggregated content.